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Talks & Seminars
Title: Distributed Programming and Querying Over Large Graphs Using GoFFish
Prof. Yogesh Simmhan, Indian Institute of Science, Bangalore
Date & Time: November 10, 2016 15:00
Venue: Conference Room, C Block, 01st Floor, Department of Computer Science and Engineering, Kanwal Rekhi (KReSIT) Building
Abstract:
This talk will focus on the programming abstractions and scalable runtimes for distributed processing of large graphs as part of the GoFFish project. Our subgraph-centric programming abstraction leverages and extends Google’s Pregel vertex-centric model while mitigating issues of message and iteration complexity. This abstraction is mapped to a distributed execution model over static clusters and elastic Cloud VMs to achieve weak scaling and also reduces the monetary cost a priori modeling of the execution. Further, we examine declarative querying over large property graphs by compiling path and reachability queries into a distributed execution over GoFFish. This graph database achieves sub-second latency through the use of cost models and indexing, and out-performs comparable open-source distributed databases. Lastly, this talk will introduce work-in-progress problems related to defining algorithms, abstractions and runtimes for dynamic and temporal graphs.
Speaker Profile:
Yogesh Simmhan is an Assistant Professor at the Department of Computational and Data Sciences at the Indian Institute of Science, Bangalore. Previously, he was a Research Assistant Professor in the Electrical Engineering Department at the University of Southern California, Los Angeles and Associate Director of the USC Center for Energy Informatics. His research explores abstractions, algorithms and applications on distributed systems. These span Cloud and Edge Computing, Distributed Graph Processing Platforms and Elastic Stream Processing to support emerging "Big Data" and Internet of Things (IoT) applications. His research advances fundamental knowledge, and offers a practitioner's insight, on building scalable and resilient systems. He has won the IEEE/ACM Supercomputing HPC Storage Challenge Award in 2008 and IEEE TCSC SCALE Challenge Award in 2012. He is a Senior Member of IEEE and ACM, Associate Editor of IEEE Transactions on Cloud Computing and a member of the IEEE Future Directions Initiative on Big Data. Yogesh has a Ph.D. in Computer Science from Indiana University and was earlier a Postdoc at Microsoft Research, San Francisco.
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